Field of the Invention
The present invention relates to an image recognition device, particularly to a technology of registering feature data in the image recognition device.
Description of the Related Art
Image recognition is a technology, in which feature data is extracted from an image and a subject in the image is distinguished (identified) from others by matching the extracted feature data against feature data of a known object previously registered in a database. The image recognition is applied to various fields including personal authentication and personal identification in which a biometric image such as a face image is used, a monitoring system that detects an intruder or a suspicious substance, a workpiece inspection in a production line, and identification of a passer or a passing vehicle in a transportation infrastructure.
FIG. 8A is a view illustrating a concept of the feature data registered in the database and a class. Usually, plural features are extracted from one image, and the feature data is expressed by a multidimensional vector (referred to as a feature vector) constructed with plural features. A space formed by the feature vector is referred to as a feature space. FIG. 8A schematically illustrates the feature space. In FIG. 8A, points A1 to A4 indicate the feature data of an object A, points B1 to B4 indicate the feature data of an object B, and points C1 to C4 indicate the feature data of an object C. Usually, the feature data is classified in each object, and registered and managed as a batch of data set (referred to as the “class”) in each object. Three classes KA to KC corresponding to the objects A to C are defined in the example of FIG. 8A.
At this point, when feature data X of an unknown object X is provided, the distinction (identification) of an object X can be regarded as a problem to determine which one of the class KA to class KC the feature data X belongs to (or not belong to). For example, a similarity between the feature data X and the feature data of each class is calculated to cause the feature data X to belong to the class having the highest similarity. In the example of FIG. 8A, because the feature data X is closest to the class KB, an identification result that the object X is the object B is obtained.
Because the image photographed with a camera is used in the image recognition, the extracted feature varies inevitably depending on a photographing condition (such as an object state (in case of a face, for example, an orientation, an expression, existence or non-existence of an accessory, makeup, and a hairstyle) and a lighting state) of the time. Therefore, a method for registering plural pieces of feature data extracted from plural images having the different photographing conditions with respect to the identical object is generally adopted in order to enhance robustness against a difference of the photographing condition to improve recognition accuracy. In other words, desirably a variation of the feature data registered in the database is enhanced in order to improve the accuracy of the image recognition.